The project is conducted in cooperation with epidemiologists and other medical staff from medical institutes and hospitals. The project will investigate machine learning techniques that are suitable for identifying epidemiological hazards, such as disease outbreaks, from near-realtime clinical data such as those generated by emergency services and emergency rooms in hospitals. For this purpose, methods of anomaly detection and time series analysis shall be used. Of particular interest in this sensitive field are methods for generating interpretable models, such as rules, that may be extracted from more complex models or generated interactively with a domain expert.